Tumor Classification in Well-Differentiated Thyroid Carcinoma and Sentinel Lymph Node Biopsy Outcomes: A Direct Correlation
Bibliographic record
Abstract
BACKGROUND: Predicting locoregional metastasis in well-differentiated thyroid carcinoma (WDTC) is a challenge for thyroid cancer surgeons. Sentinel lymph node biopsy (SLNB) has been shown to be an effective predictive tool. To our knowledge, primary tumor (T) classification has yet to be studied with regard to SLNB. We hypothesized that larger primary tumors would correlate with the rate of malignancy in SLNBs. METHODS: A retrospective chart review was conducted on patients operated for WDTC at the McGill Thyroid Cancer Center over a 36-month period. Patients who underwent a total thyroidectomy and SLNB for WDTC were included in this study. RESULTS: A total of 311 patients were included and separated into two groups (236 negative and 75 positive SLNBs). Among patients with negative SLNBs, 65% had T1 primary tumors, 17% T2, 16% T3, and 2% T4, whereas 18% of patients with positive SLNBs had T1 primary tumors, 5% T2, 45% T3, and 32% T4 (p<0.001). Patients under the age of 45 years had a higher rate of positive SLNs (36% in those <45 years vs. 17% in those ≥ 45 years; p<0.001). CONCLUSIONS: Age (<45 years) and higher T category were found to be associated with a higher rate of positive SLNBs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".